J Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83:363--378, 1996.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....a consistent view of the world. This demand is often complicated by the fact that such agents receive conflicting pieces of information from different sources. The process of combining possibly inconsistent pieces of information, known as merging, has started to receive more attention recently [7, 1, 2, 5, 6, 13, 12, 15]. In this paper we propose a framework for the modelling of merging operations. The proposal has its roots in the work of Spohn [14] Unlike most approaches we adopt a description of merging on the level of epistemic states instead of knowledge bases. In section 2 we give a brief introduction to ....

J. Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83(2):363- 378, 1996.

....knowledge knows that b is true whereas none of the expert knows it. This was called implicit knowledge in [8] However, simply put these knowledge bases together is a wrong way since there could be contradictions between some experts. Some logical characterizations of merging have been proposed [18, 19, 13, 14, 16, 15, 11]. In this paper we extend these works by proposing a logical characterization when the result of the merging has to obey to a set of integrity constraints. We de ne two subclasses of merging operators, namely majority merging and arbitration operators. The former striving to satisfy a maximum of ....

J. Lin. Integration of weighted knowledge bases. Arti cial Intelligence, 83(2):363{ 378, 1996.

....that merging ought to be performed on epistemic states instead of knowledge bases. An epistemic state contains, not just the beliefs of an agent, but also an indication of the strength of these beliefs. Merging operations of different kinds have been proposed by various authors. See, for example, [Lin, 1996; Revesz, 1997; Konieczny and Pino Perez, 1998; Benferhat et al. 1999; Meyer, 2000; Maynard Reid and Shoham, 1998; Maynard Reid and Lehmann, 2000] Social choice theory [Arrow, 1963; Sen, 1986] is a research area which addresses problems that are similar to those in merging. Its aims are to ....

J. Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83(2):363--378, 1996.

....that merging ought to be performed on epistemic states instead of knowledge bases. An epistemic state contains, not just the beliefs of an agent, but also an indication of the strength of these beliefs. Merging operations of different kinds have been proposed by various authors. See, for example, [Lin, 1996; Revesz, 1997; Konieczny and Pino Perez, 1998; Benferhat et al. 1999; Meyer, 2000; Maynard Reid and Shoham, 1998; Maynard Reid and Lehmann, 2000] Social choice theory [Arrow, 1963; Sen, 1986] is a research area which addresses problems that are similar to those in merging. Its aims are to ....

J. Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83(2):363--378, 1996.

.... an inconsistency, we can simply do it) There is no consensus, in the literature, about the name to give to the operation of combining knowledge bases with the same degree of reliability: Revesz [15] and Liberatore and Schaerf [10, 11] use the name arbitration, while Lin and Mendelzon [13] and Lin [12] prefer the term merging. Konieczny and Pino Perez [8] show that there is a semantical distinction between arbitration and merging. Namely, they show that there are scenarios in which arbitration is more appropriate, and other ones in which the operation to perform is merging. This issue is ....

....2 does not extend our knowledge about the previous time point. The litmus test example [3] shows a scenario in which such backward inference should be done. Let us now consider merging, or arbitration. This is the operation of integrating two knowledge bases having the same degree of reliability [15, 13, 10, 12, 11, 8]. The assumption is that the two knowledge bases refer to the same time point. Let the two knowledge bases be represented by the formulas K 1 and K 2 . It is straightforward to express them in brels: KB = # source(1) K 1 , source(1) K 2 # The result of arbitration or merging is the ....

J. Lin. Integration of Weighted Knowledge Bases. Artificial Intelligence, 83(2):363--378, 1996.

....of change, we propose to take the propositional variable as such a unit, as Dalal says in [Dal88] Change in truth value of a single symbol can be considered as the smallest unit of change , we want to apply this to arbitration. Lin and Mendelzon proposed a theory merging by majority operator [LMa, Lin96] which solves conflicts between knowledge bases by taking the majority into account. Their theory merging operators are what we call majority operators. The paper is organized as follows: in section 2 we give some definitions and state some notations. In section 3 we propose postulates for ....

J. Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83(2):363-- 378, 1996.

....unit of change, we propose to take the propositional letter as such a unit, as Dalal says in [Dal88] Change in truth value of a single symbol can be considered as the smallest unit of change , we want to apply this to merging. Lin and Mendelzon proposed a theory merging by majority operator [LM, Lin96] which solves con icts between knowledge bases by taking the majority into account. Their theory merging operators are what we call majority operators. In section 2 we give some de nitions and state some notations. In section 3 we propose a logical de nition of merging operators with integrity ....

J. Lin. Integration of weighted knowledge bases. Articial Intelligence, 83(2):363-378, 1996.

....reasoning abilities that can make decision making realistically useful. 56] and [54] are examples of previous work exploring negotiation as a means to mediate among conflicting agents. Some recent approaches to conflict resolution use prioritized defaults [27] or model theoretic solutions [38]. They provide semantic accounts of conflict resolution based on a single order of precedence of beliefs. This is very useful, but still has to address the issues of computational architectures and negotiation. 7. Related Work Our coordination system is related to a number of other efforts ....

J. Lin. Integration of Weighted Knowledge Bases. To appear in Artificial Intelligence Journal.

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Jinxin Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83/2:363--378, 1996.

....Databases under Constraints Jinxin Lin Alberto O. Mendelzon Dept. of Computer Science University of Toronto Toronto, CANADA M5S 1A4 flin,mendelg db.toronto.edu June 3, 1996 Abstract The problem of integrating information from conflicting sources comes up in many current applications, such as cooperative information systems, heterogeneous databases, and multi agent systems. We model this by the operation of merging first order theories. We propose a formal ....

Jinxin Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83/2:363--378, 1996.

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J Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83:363--378, 1996.

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J. Lin. Integration of Weighted Knowledge Bases. Artificial Intelligence, 83(2):363--378, 1996.

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J. Lin. Integration of weighted knowledge bases. Artificial Intelligence, 83(2):363--378, 1996.

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